ChatGPT answers, unedited

Yes. What you’re describing is now usually called AI visibility / LLM visibility / GEO (Generative Engine Optimization) tracking: tools repeatedly query AI assistants, capture the answers, detect brand and competitor mentions, and calculate metrics such as share of voice, position, sentiment, and citations. AI Visibility Software ModelMention

A few tools worth looking at:

• tryprofound.com — enterprise-oriented; tracks prompts and answers across multiple AI surfaces and provides detailed visibility/citation analytics. Tomek Sikora DataDab
• peec.ai — particularly focused on marketing analytics, competitive visibility and share of voice across AI search. Arbling
• otterly.ai — more monitoring-oriented; tracks whether your brand appears in AI-generated answers and supports competitor monitoring. Toolsolved DataDab
• ahrefs.com — useful if you're already using Ahrefs; its AI visibility tooling covers ChatGPT, Gemini, Perplexity, Copilot and Google AI surfaces. Ahrefs
• searchprism.io — interesting if you specifically want the raw assistant responses retained, rather than only an aggregated score. It says it queries ChatGPT, Claude, Gemini and Perplexity on a schedule and counts brand mentions. Prism

One important distinction

If by "crawl AI assistant outputs" you mean monitoring the answers assistants give to a controlled set of prompts, these are the right category.

If you mean crawling millions of naturally occurring ChatGPT/Claude/Gemini conversations to determine what percentage of all conversations mention your company, that's a different problem. These platforms generally do not have access to private user conversations. Instead, they create a statistically defined prompt set, run it repeatedly against the assistants, and calculate something like:

Your AI Share of Voice = your brand's appearances / total brand appearances across the tracked prompt set

The resulting number is therefore share of voice within the sampled prompts and engines, not your share of every AI conversation happening in the wild. This distinction is important when presenting the metric internally. RocketBlue

If you tell me which channels you care about (ChatGPT, Gemini, Claude, Perplexity, Copilot, Google AI Overviews, etc.) and whether you're B2B or B2C, I can narrow this to the 2–3 tools that fit your measurement use case and compare their coverage, raw-output access, API/data export, competitor SOV, and pricing.

If by “share of voice” you mean how often your brand is mentioned/recommended/cited in AI-generated answers relative to competitors, you’re looking for an AI visibility / GEO / share-of-model monitoring platform.

A few current options:

• otterly.ai — particularly relevant if you want broad channel coverage. It tracks prompts across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, and reports share of voice, mentions, sentiment, rankings and citations. Otterly Otterly
• peec.ai — focused heavily on AI visibility and competitive SOV. It measures the percentage of AI responses mentioning your brand, average position, sentiment and share of voice versus competitors. Peec AI
• tryprofound.com — another major enterprise-oriented option for monitoring brand presence across AI answer engines.
• scrunchai.com — worth considering if you want monitoring combined with optimization/action capabilities.

One important distinction

These tools generally don't crawl every spontaneous conversation occurring inside ChatGPT/Claude/etc. Instead, they maintain a controlled set of prompts, run those prompts against the AI engines, capture the answers, and calculate metrics such as:

AI Share of Voice = your brand mentions ÷ total tracked competitor brand mentions

For example, if you run 1,000 category-relevant prompts and your brand appears in 180 answers while competitors collectively appear 820 times, the platform can calculate your relative SOV. Otterly explicitly describes running prompt sets, storing answers, and scoring which brands were named and in what order. Otterly

If your goal is “What percentage of the conversations a prospective customer has with AI assistants result in our brand being mentioned?”, I'd pay particular attention to prompt methodology, sampling frequency, geographic/personalization controls, and whether they distinguish brand coverage from true SOV. Those methodological differences can materially change the number. Influencers Time

If you tell me your company/category and which channels you mean by “voice” (e.g. ChatGPT voice mode, Alexa/Siri, Gemini, Perplexity, Claude, AI Overviews), I can map the available tools against those channels and identify which ones actually measure what you need.

Tools in this category are usually called AI visibility / Generative Engine Optimization (GEO) / AI share-of-voice platforms. They don’t “crawl” private assistant chats; instead, they run controlled prompt sets against AI assistants, capture outputs, and calculate brand mentions, rankings, citations, and competitor share. Visibility.so Foglift

Common options:

• Profound — tracks brand presence in AI-generated answers and measures competitive visibility. Foglift
• Seerly — runs prompts across ChatGPT, Perplexity, Claude, and others to show visibility and share-of-voice trends. Seerly
• Visibility.so — monitors how brands appear in AI answers and compares competitors. Visibility.so
• Profound, Otterly, and similar tools are often used for AI-search monitoring benchmarks. Foglift

For voice channels (Alexa, Siri, Google Assistant, in-car assistants), the tooling is less mature. You typically need a combination of:

• speech assistant testing frameworks,
• conversation analytics platforms,
• your own synthetic-query harness that records assistant responses,
• NLP classification to score brand mentions and recommendations.

For an enterprise setup, the usual architecture is:

1. Build a prompt/query library from customer intents.
2. Run queries across ChatGPT, Claude, Gemini, Perplexity, voice assistants, etc.
3. Store responses.
4. Extract entities, sentiment, ranking position, citations, and recommendations.
5. Calculate share of voice:

brand mentions ÷ total competitor mentions within the tracked answer set.

If you mean monitoring your own customers’ real voice-assistant interactions (call center/IVR/agent conversations) rather than synthetic AI answers, that is a different tool category.

If you mean “crawl AI assistant outputs (ChatGPT, Gemini, Claude, Perplexity, etc.) and calculate our brand’s share of voice”, you’re looking for an AI visibility / Generative Engine Optimization (GEO) monitoring platform, not a traditional web crawler.

Tools in this category include:

For voice channels (Alexa, Siri, Google Assistant, in-car assistants, call-center AI), the tooling is less mature. You typically need a combination of:

• Conversation analytics (transcripts from voice assistants/contact centers)
• Speech analytics (mentions, sentiment, intent, competitor mentions)
• LLM answer monitoring (for text-based assistants)

A robust measurement stack usually looks like:

1. Define a prompt/query universe

• “best [category]”
• “compare [brand] vs competitors”
• “what should I buy for [use case]”
• Run those prompts across:

• ChatGPT
• Gemini
• Claude
• Perplexity
• AI Overviews / AI search experiences
• Extract:

• Brand mention rate
• Recommendation rate
• Position/ranking in answers
• Citation frequency
• Sentiment
• Competitor share
• Calculate:

AI Share of Voice = your brand mentions ÷ total tracked brand mentions in AI answers

Most vendors above focus on chat/search assistants rather than true voice assistants. AI SOV measurement is currently centered on generated answers and citations rather than audio assistant responses. theStacc Shadow

If you’re building this internally, the architecture is usually:
prompt crawler → assistant/API runners → response parser → entity extraction → SOV dashboard.

For a large enterprise PR/marketing team, I’d shortlist Profound, Semrush, Ahrefs, or Peec. For a custom analytics product, I’d build on top of model APIs and store every answer snapshot for longitudinal comparison. Shadow Semrush

If you mean “crawl AI assistant answers (ChatGPT, Gemini, Claude, Perplexity, etc.) and calculate our brand’s share of voice (SoV)”, you’re looking for an AI visibility / generative engine optimization (GEO) monitoring platform, not a traditional web crawler. These tools typically run a library of prompts, capture AI responses, extract brand mentions/citations, and benchmark you against competitors. Semrush Shadow

Some leading options:

For voice channels (Alexa, Siri, Google Assistant, automotive assistants, call-center AI), the landscape is less mature. You generally need a combination of:

• Conversation testing platforms (run standardized spoken queries and capture responses)
• Speech analytics (for owned call-center/voice assistant interactions)
• Custom evaluation pipelines that score: - whether your brand is mentioned
• rank/order of recommendation
• sentiment
• accuracy
• competitor mentions
• source attribution

A typical enterprise setup looks like:

1. Build a prompt/query set:

• “Best CRM for startups”
• “Who are the top providers of X?”
• “Compare Brand A vs Brand B”
• Run it daily/weekly across:

• ChatGPT
• Claude
• Gemini
• Perplexity
• AI Overviews / AI Mode
• voice assistants where relevant
• Extract:

• Mention share = your mentions ÷ total brand mentions
• Answer share = % of prompts where you appear
• Citation share = % of cited sources pointing to you
• Recommendation rank = average position when listed

theStacc PreferIf you’re building this internally, the architecture is usually:

• LLM/API runners → collect answers
• browser automation where APIs are unavailable
• response parser → identify entities
• scoring engine → calculate SoV
• dashboard → track trends

For a large brand/enterprise, I’d shortlist Profound, Semrush Enterprise AIO, and Scrunch. For a lean marketing/GEO team, Peec AI or Otterly.AI are closer fits. Semrush Shadow

If you mean voice assistants specifically (Alexa/Siri/Google Assistant) rather than AI chat/search answers, the recommended toolset is different.

Yes. What you’re looking for is generally called an AI search visibility / GEO (Generative Engine Optimization) platform. These tools repeatedly query AI assistants, capture the answers, extract brand mentions/citations, and calculate competitive share of voice.

My shortlist

• ahrefs.com — probably the best fit if you want a mature SEO platform plus AI visibility. It tracks ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews/AI Mode, custom prompts, mentions, citations, competitors and AI Share of Voice. Ahrefs
• tryprofound.com — strong enterprise-oriented option for monitoring how brands appear across generative engines and analyzing the sources AI uses.
• otterly.ai — purpose-built AI search monitoring, with strong emphasis on tracking mentions/citations and competitive visibility.
• peec.ai — focused on AI-search visibility and competitive benchmarking across multiple engines.
• modelmention.io — particularly straightforward if your main requirement is visibility + position + share of voice + sentiment + citations across ChatGPT, Gemini and Perplexity. ModelMention
• asklab.ai — queries leading AI engines, parses the responses, and aggregates mentions, citations, sentiment and share of voice. AskLab

If you mean voice assistants too

There's an important distinction. Most of these products are really measuring AI/search answers, not traditional voice assistants such as Alexa, Siri or Google Assistant.

For a true "share of voice across chat + voice" measurement system, I'd look for a platform/API that can:

1. Maintain a controlled set of customer prompts.
2. Run them across ChatGPT, Gemini, Claude, Perplexity, Copilot, etc.
3. Capture the actual generated answer.
4. Record whether your brand was mentioned.
5. Extract competitor mentions.
6. Capture cited/source URLs.
7. Score position/prominence, not just binary mention.
8. Repeat the same prompts over time to calculate SOV trends.
9. Segment by engine, geography, prompt type and customer journey stage.

That's important because AI answers are nondeterministic; a single query isn't a reliable SOV measurement. Current methodologies recommend multiple runs per prompt and reporting the aggregate rather than treating one answer as definitive. OrganiKPI Verity Score

If you're building this capability internally, rather than buying a dashboard, I can also map out the API/tool stack for actually crawling ChatGPT, Gemini, Claude, Perplexity and voice channels and computing SOV, including which providers permit automated querying and what the data pipeline would look like.

Yes. What you’re looking for is generally called an AI visibility / GEO (Generative Engine Optimization) platform. These tools repeatedly run a controlled set of prompts through AI assistants, capture the answers, extract brand/competitor mentions and citations, and calculate AI share of voice.

A few worth evaluating:

• demandsphere.com — strongest enterprise-style option from what I found. Tracks ChatGPT, Perplexity, Gemini, Copilot, Google AI Overviews/AI Mode, Grok, DeepSeek and Meta AI, with full response capture, mentions, citations, sentiment and competitor share of voice. DemandSphere
• seerly.app — specifically emphasizes live prompt runs, competitor share of voice, trends, and per-engine visibility across ChatGPT, Perplexity, Claude and others. Seerly
• getveritas.io — tracks brand mentions/citations and SOV across ChatGPT, Perplexity, Gemini and Google AI Overviews. Veritas
• foglift.io — interesting if you want an auditable methodology: it retains the underlying prompt, answer, competitor mentions, citations and measurement window behind the SOV calculation. It also offers an API. Foglift Foglift
• siftly.ai — combines AI brand monitoring, prompt tracking, citation tracking and SOV, with coverage of ChatGPT, Gemini, Perplexity and Google AI Overviews. Siftly

One important distinction

If by "crawl AI assistant outputs" you literally mean collecting outputs from assistants at scale, rather than simply monitoring your brand, I'd prioritize a platform that gives you raw response-level data/API access.

For measuring SOV properly, you ideally want:

fixed prompt set → query multiple assistants → store complete responses → extract brands → identify position/mention/citation → normalize by engine → calculate SOV → trend over time

That matters because a headline "37% SOV" is only meaningful if you can see which prompts produced it, which competitors were included, which engines were queried, and the underlying answers. Foglift explicitly makes this evidence-level approach part of its methodology. Foglift

If you tell me whether this is for your own brand, an agency reporting product, or building your own measurement stack, I can narrow this to the 3 best tools and compare pricing, API access, assistant coverage, raw-output access, and SOV methodology.

If you mean measuring your brand’s share of voice (SOV) inside AI assistant answers (ChatGPT, Gemini, Claude, Perplexity, Copilot, Google AI Overviews), you’re looking for an AI visibility / Generative Engine Optimization (GEO) monitoring tool rather than a traditional SEO crawler.

Some tools in this category:

For a serious voice + chat channel SOV program, I’d evaluate tools against these capabilities:

• Prompt universe management

• Can you define the exact customer questions you care about?
• Example: “best CRM for startups,” “top running shoes for flat feet,” “alternatives to X.”
• Multi-model coverage

• ChatGPT
• Gemini
• Claude
• Perplexity
• Copilot
• Google AI Overviews / AI Mode
• Competitive SOV calculation

• % of answers where your brand appears
• % where competitors appear
• rank/order of recommendations
• sentiment or recommendation strength
• Citation/source analysis

• Which websites, reviews, Reddit threads, articles, and pages cause models to mention you.
• Historical tracking

• “Our AI answer share was 8% in January and 19% in June.”

If you mean voice assistants specifically (Alexa, Siri, Google Assistant spoken responses), that is a different measurement problem. Most GEO tools focus on text AI answers, not smart-speaker voice results. For voice assistants you typically need a custom testing framework: a prompt library + device/API testing + transcription + answer classification.

For most marketing teams today, the closest equivalent to “AI share of voice” is:
tracked prompts → run across AI assistants → collect answers → extract mentions/citations → calculate SOV vs competitors. Zumi DeepSmith

If you’re building this in-house, the stack is usually:

• LLM/API access for answer collection
• prompt scheduler
• crawler/parser for citations
• entity recognition model
• SOV scoring dashboard (Looker, Tableau, Power BI, etc.)

I can also give you a vendor shortlist by enterprise vs startup budget or a DIY architecture for crawling AI assistant outputs.

Yes. What you’re looking for is generally called AI search visibility / GEO monitoring / AI Share of Voice (SOV). These tools repeatedly run a controlled prompt set against AI assistants, collect the answers and citations, and calculate how often your brand appears relative to competitors. theStacc OrganiKPI

Tools I’d shortlist

• tryprofound.com — strong enterprise option for monitoring AI answers, citations, competitors, and brand visibility across multiple AI engines.
• ahrefs.com — particularly interesting if you want a very large prompt dataset. Ahrefs says its index is based on 461M+ real prompts across ChatGPT, Gemini, Perplexity, Copilot and Google's AI surfaces. Ahrefs
• otterly.ai — focused specifically on AI-search monitoring and competitor visibility.
• peec.ai — good fit for agencies/marketing teams tracking multiple brands and AI engines.
• scrunch.com — more enterprise-oriented, with AI crawler/visibility monitoring.
• rankseer.com — explicitly calculates Share of Voice across ChatGPT, Perplexity and Gemini and compares competitors. Rankseer
• modelmention.io — tracks visibility, SOV, sentiment and citations across ChatGPT, Gemini and Perplexity. ModelMention

One important distinction

If by “voice and chat channels” you literally mean voice assistants (e.g. Siri, Alexa, Google Assistant) as well as chat interfaces, that's a somewhat different requirement. Most of the current “AI SOV” platforms primarily measure text-generated answers from ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews/AI Mode, etc. Honeyb

For chat/AI search, I'd start by evaluating Profound, Ahrefs, Otterly and Peec.

For a serious measurement program, I would also insist that the vendor lets you see the raw answers, not just a proprietary visibility score. AI responses are nondeterministic, so credible measurement needs repeated runs, a fixed prompt panel, engine-by-engine reporting, competitor comparison, and citation/source tracking. Verity Score Clear Cited

If you tell me your company/category and which channels you mean by “voice” (Siri/Alexa/Google Assistant vs. spoken ChatGPT/Gemini), I can narrow this to the 3 best vendors and compare their crawling methodology, AI coverage, SOV calculation, API/export capabilities, and pricing.

Yes — the category you’re looking for is generally called AI visibility / LLM visibility / Generative Engine Optimization (GEO) tracking. These tools repeatedly run a defined set of buyer prompts through AI assistants, capture the actual answers, and calculate mention rate, citation rate, rankings, and competitor share of voice. theStacc Rank.ai

Tools I'd shortlist

• tryprofound.com — strong enterprise-oriented option for monitoring AI search/assistant visibility and competitive presence.
• otterly.ai — broad engine coverage and a more SEO-like monitoring workflow. A recent 2026 comparison specifically highlights its multi-engine monitoring. Pinggy
• peec.ai — focused on GEO/AI-search visibility and competitor comparisons.
• mention.network — particularly interesting if share of voice is the primary KPI; it explicitly breaks SOV down by ChatGPT, Gemini, Perplexity, DeepSeek, Grok, etc. Mention Network
• getmint.ai — tracks ChatGPT, Gemini, Perplexity, Claude and Google AI Overviews, with mention, citation, sentiment and SOV metrics. GetMint
• rank.ai — interesting if you want explicit share of voice vs. competitors at the prompt/surface level and daily monitoring. Rank.ai

One important distinction

If by "voice channels" you literally mean spoken AI assistants — e.g. voice conversations with ChatGPT, Gemini, Siri, Alexa, etc. — that's a harder problem than standard AI-search monitoring.

Most of these platforms measure the textual answer generated by the underlying AI/search surface, not the audio interaction itself. For example, Rank.ai describes its methodology as repeatedly sending buyer prompts to each provider and parsing the resulting responses. Rank.ai

So if you're trying to measure something like:

"When consumers ask an AI assistant about our category, what percentage of the recommendations/mentions are us vs. competitors?"

I'd look particularly closely at Profound, Otterly, Peec, and Mention Network.

If you tell me whether you mean ChatGPT/Gemini/Perplexity chat, Google AI Overviews/AI Mode, or actual voice assistants, I can narrow this to the 3 best tools and compare their coverage, SOV methodology, API/export capabilities, and pricing.

Yes — there’s now a fairly mature category for this. The terms to look for are AI visibility, LLM visibility, AI search monitoring, or Generative Engine Optimization (GEO).

If your goal is specifically “crawl AI assistant answers and calculate our share of voice versus competitors,” I’d shortlist:

• ahrefs.com — probably the strongest choice if you want scale. It analyzes hundreds of millions of prompts across ChatGPT, Gemini, Perplexity, Copilot and Google AI, with brand mentions/citations and competitor benchmarking. Ahrefs Ahrefs
• tryprofound.com — a purpose-built enterprise AI-search visibility platform; particularly worth evaluating if this is for a larger brand/marketing organization.
• mentionsflow.com — explicitly tracks mentions, citations, comparisons and share of voice across ChatGPT, Claude, Gemini, Perplexity and Google AI Overviews. Mentions Flow
• modelmention.io — focused on whether ChatGPT/Gemini/Perplexity recommend you versus competitors, with visibility, position, SOV, sentiment and citation tracking. ModelMention
• useklarity.co — tracks a defined prompt set daily across ChatGPT, Gemini and Perplexity and reports SOV, competitor position and sentiment. Klarity
• visibility.so — particularly interesting if you want the actual generated answers at prompt level, alongside competitor SOV and source rankings. Visibility.so

One important distinction

If by “voice and chat channels” you mean AI assistants themselves — ChatGPT, Gemini, Claude, Perplexity, Copilot, Google AI Overviews, etc. — these tools are exactly the category you're after.

If you mean voice assistants too — e.g. Siri, Alexa, Google Assistant, conversational call-center bots — that's a different and less mature measurement problem. Most of the products above measure text AI answers, not what a voice assistant says in an actual spoken interaction.

For SOV, the basic measurement is usually something like:

Your SOV = your mentions ÷ total competitor mentions across the same sampled AI answers

A good system should let you drill down from overall SOV → engine → prompt → individual answer → mention/citation → competitor. That matters because AI answers are nondeterministic, so simply asking an LLM a question once isn't a particularly reliable measurement. Some current methodologies recommend repeated runs and fixed prompt panels for that reason. Citations OrganiKPI

If you're evaluating vendors for a business, I'd start with Ahrefs + Profound + MentionsFlow and compare them on custom prompt coverage, actual answer capture, competitor tracking, historical data, API/export, and whether they distinguish “mentioned” from “recommended” and “cited.” Those distinctions can materially change your SOV number.

Yes. What you’re describing is generally called AI visibility / Generative Engine Optimization (GEO) tracking: tools repeatedly run a fixed set of buyer prompts against AI assistants, capture the responses, identify brand/competitor mentions and citations, and calculate share of voice (SOV).

A few worth evaluating:

• semrush.com — probably the strongest choice if you already use Semrush. It explicitly calculates AI SOV using brand mentions and position, and covers ChatGPT, Google AI Overviews/AI Mode, Perplexity and Gemini. Semrush
• tryprofound.com — enterprise-focused AI search/answer-engine monitoring; a strong option for larger brands wanting systematic monitoring and competitive intelligence.
• otterly.ai — purpose-built for AI search visibility and tracking brand mentions across answer engines.
• peec.ai — focused specifically on AI-search visibility, prompt tracking, competitors and SOV.
• chatobserver.com — particularly close to your wording: it runs buyer questions against ChatGPT, Gemini, Claude, Perplexity and AI Overviews, recording the full answers, citations and competitors, then reports SOV. Chatobserver
• asklab.ai — tracks ChatGPT, Gemini, Claude and Perplexity and provides mentions, citations, sentiment, rankings and SOV. AskLab
• zumihq.com — useful if you want granular source/citation analysis in addition to SOV; it tracks which exact URLs are feeding AI answers. Zumi

If you mean actual voice assistants

There’s an important distinction. Most of these products measure AI-generated text answers, even when the user ultimately hears the answer spoken aloud. They aren't necessarily measuring the output of voice interfaces such as Siri, Alexa, or voice-mode interactions independently.

If your goal is:

“When consumers ask an AI assistant verbally for recommendations, what % of the resulting answers mention/recommend our brand versus competitors?”

I'd prioritize a platform that can execute prompts against the actual assistant/channel and archive the raw response, rather than simply crawling web pages.

For a serious share-of-voice measurement system, I'd want these capabilities:

1. Prompt panel — hundreds/thousands of real buyer questions.
2. Multi-engine execution — ChatGPT, Gemini, Claude, Perplexity, Google AI Mode/Overviews, Copilot, etc.
3. Raw response capture — preserve exactly what the assistant answered.
4. Entity extraction — identify your brand + competitors.
5. Position weighting — #1 recommendation should count more than a passing mention.
6. Citation/source extraction — identify which sites caused the recommendation.
7. Voice/channel separation — distinguish typed vs voice interactions where possible.
8. Geography/persona/device controls — answers can vary substantially.
9. Repeated sampling — AI answers are nondeterministic, so one run isn't enough.
10. Historical SOV — trend your percentage over weeks/months.

For example, a robust metric could be:

AI SOV = weighted mentions of your brand ÷ weighted mentions of all tracked brands

rather than simply counting whether your brand appeared. Current AI-visibility methodologies increasingly use mention rate, position, citation share and competitive context rather than a simple binary “mentioned/not mentioned” metric. AirShelf.AI Foglift

If you tell me your industry and which channels you mean by “voice and chat” (e.g. ChatGPT Voice, Gemini, Siri, Alexa, Perplexity, Copilot), I can narrow this to the 3 best platforms and compare their actual crawling/measurement methodology, API access, and pricing.

AI SOV = weighted mentions of your brand ÷ weighted mentions of all tracked brands

rather than simply counting whether your brand appeared. Current AI-visibility methodologies increasingly use mention rate, position, citation share and competitive context rather than a simple binary “mentioned/not mentioned” metric.

Yes. If by “crawl AI assistant outputs” you mean repeatedly query the assistants, capture the actual answers, identify brand/competitor mentions and citations, and calculate share of voice (SOV), there are several purpose-built platforms.

Best fits

• tryprofound.com — probably the strongest enterprise-oriented option. It queries the front-end experiences real users see, including ChatGPT, Perplexity, Claude, Copilot, Google AI Overviews/AI Mode, Gemini, Grok and DeepSeek, then reports visibility, SOV, sentiment, citations and competitor rankings. Profound
• scrunch.com — very directly aligned with your wording. It collects real AI responses, detects brand mentions, and calculates competitive presence/SOV across nine AI platforms. It also lets you drill from overall SOV → individual prompts → citations. Scrunch Scrunch
• ahrefs.com — interesting if you also want traditional SEO/search data alongside AI visibility. Its current index uses hundreds of millions of modeled prompts across ChatGPT, Gemini, Copilot, Perplexity and Google AI. Ahrefs
• agentgeo.org — particularly interesting if you want an API/raw-answer approach. It returns the actual assistant answer as JSON, after which you can calculate your own SOV in an auditable way. AgentGEO
• gemrank.co — focused on monitoring how ChatGPT, Gemini, Claude and Perplexity talk about and rank your brand, including visibility and competitor comparisons. Gem Rank

One important distinction

If you're building a serious “AI share of voice” measurement system, I'd separate two things:

1. Answer SOV:

Of the AI answers to our target questions, what % mention us vs. competitors?

2. Citation/source SOV:

Of the sources AI assistants use to construct those answers, what % are ours vs. competitors/third parties?

Scrunch explicitly supports both, while Profound also tracks SOV alongside citations, sentiment and rankings. Scrunch Profound

For example, your metric could be:

Brand SOV = answers mentioning Brand ÷ total answers containing any tracked competitor

I'd also segment it by assistant × prompt/topic × geography × date × competitor, because one aggregate SOV number can hide major differences between ChatGPT, Gemini, Perplexity, etc.

If you're evaluating vendors for your company, I'd shortlist Profound, Scrunch, and AgentGEO first—Profound for enterprise intelligence, Scrunch for ready-made SOV analytics, and AgentGEO if you want the underlying answers/API and intend to build your own measurement layer. A recent 2026 benchmark also compares these types of tools across ChatGPT, Perplexity, Gemini and other engines. Foglift

If you tell me whether you're looking to buy a tool or build this capability yourself, I can give you a side-by-side of the best options, including pricing, APIs, channels covered, how they calculate SOV, and whether they can monitor voice/audio assistants rather than just text chat.

Yes — the category you’re looking for is AI visibility / GEO (Generative Engine Optimization) monitoring. These tools run a fixed set of prompts against AI assistants, capture the actual answers, identify brand mentions/citations and competitors, and calculate AI share of voice.

Strong options

• tryprofound.com — probably the one I'd investigate first for enterprise-grade monitoring. Strong focus on AI search/answer visibility and citation intelligence.
• ahrefs.com — particularly interesting if you already use Ahrefs. It says its index is based on 468M+ real prompts across ChatGPT, Gemini, Perplexity, Copilot and Google AI surfaces. Ahrefs
• otterly.ai — purpose-built AI visibility tracking; good candidate for straightforward brand/competitor monitoring.
• peec.ai — another dedicated GEO platform with multi-engine tracking.
• seerly.app — explicitly tracks live AI responses across ChatGPT, Perplexity, Claude and others, with share-of-voice and engine-level breakdowns. Seerly
• asklab.ai — tracks prompts, parses responses for mentions/citations/sentiment, and calculates competitive share of voice. AskLab

There are also newer tools such as agentgeo.org, which takes an interesting approach: it actually fetches the AI answers and returns them as data, leaving the SOV calculation auditable in your own code. It supports ChatGPT, Perplexity, Gemini, Google AI Overviews/AI Mode and Copilot. AgentGEO

One important distinction

If by “crawl AI assistant outputs” you mean literally collecting the responses themselves, rather than relying on a proprietary visibility score, I'd favor a platform/API that gives you the raw answer + citations + timestamp + engine + prompt.

Then you can calculate something like:

AI SOV = your brand mentions ÷ all tracked competitor mentions

and separately measure citation share, position/prominence, sentiment, and recommendation rate. This is important because AI responses are nondeterministic, so a serious measurement program should run multiple observations per prompt rather than treating one answer as ground truth. OrganiKPI Verity Score

If you tell me whether you're looking for (a) a SaaS tool to buy, (b) an API you can integrate into your own product, or (c) a tool that can monitor voice assistants specifically (Siri/Alexa/Gemini voice), I can narrow this to the 3 best options and compare their actual crawling method, channels, API access, pricing, and SOV methodology.

Yes. The category you’re looking for is generally called AI visibility / LLM visibility / Generative Engine Optimization (GEO) monitoring. These platforms repeatedly query AI assistants, capture the answers, identify brand mentions/citations and competitors, and calculate share of voice.

Best fits

• ahrefs.com — probably the strongest all-around option. It measures AI Share of Voice from actual AI responses and covers ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews and AI Mode. It also distinguishes mentions from citations and supports custom prompts. Ahrefs
• meltwater.com — particularly interesting if you already use Meltwater for brand/social intelligence. Its research tracks thousands of prompts across eight LLM/search surfaces, including ChatGPT, Claude, Gemini, Perplexity, Grok and Google's AI surfaces. Meltwater
• seerly.app — focused specifically on live AI responses, competitor visibility and share of voice. It lets you drill into individual responses and see the sources cited. Seerly
• kitbase.dev — good if you want a more prompt-driven measurement system. It calculates presence rate and normalized share of voice from actual answers to your chosen prompts. Kitbase
• cloro.dev — worth looking at if you're building your own analytics/dashboard rather than buying a marketing UI. It exposes parsed AI responses, citations, source URLs and positions through an API that you can aggregate into your own SOV calculations. cloro

If by “voice” you literally mean voice assistants

There’s an important distinction. Most of these tools measure text responses from AI assistants, not the audio output of Alexa/Siri/Google Assistant/etc. If your definition of SOV is:

“When a consumer asks an AI/voice assistant a category question, what percentage of the resulting recommendations are our brand?”

then I would look at Ahrefs Brand Radar or a custom measurement stack using an API like cloro, rather than a traditional SEO rank tracker.

A good SOV calculation would look roughly like:

Your AI SOV = your brand mentions/recommendations ÷ total brand mentions/recommendations across the competitive set

with separate metrics for mention rate, recommendation rate, citation rate, position, sentiment, and SOV by prompt × model × geography.

If you tell me your industry and which channels you mean by “voice and chat” (e.g. ChatGPT, Gemini, Claude, Perplexity, Alexa, Siri, Google Assistant), I can narrow this down to the 3 platforms I'd shortlist and compare their coverage, API access, crawling methodology, and pricing.

Yes — the category you want is AI visibility / AI search monitoring, sometimes called GEO monitoring or Share of AI Voice.

Best fits

• otterly.ai — probably the closest match to your description. It runs a defined prompt set through ChatGPT, Perplexity, Gemini, Google AI, Copilot and Claude, captures the answers, and calculates brand mentions, position, sentiment, citations, and share of voice vs. competitors. Otterly Otterly
• tryprofound.com — stronger enterprise-oriented option if you need deeper AI-search analytics and larger-scale monitoring. It is one of the major dedicated AI visibility platforms. Foglift Refine AI
• ahrefs.com — interesting if you're already an Ahrefs customer. It benchmarks visibility using a very large prompt corpus and covers ChatGPT, Gemini, Perplexity, Copilot and Google's AI experiences. Ahrefs
• meltwater.com — worth considering if by "voice and chat channels" you also mean social/video/source ecosystems feeding AI answers, rather than just measuring the answers themselves. Meltwater is tracking eight major AI systems and analyzing the sources they use. Meltwater

One important distinction

If by "crawl AI assistant outputs" you mean:

"Give it 500 buyer questions, repeatedly query ChatGPT/Gemini/Claude/Perplexity, save every response, identify every brand mentioned, weight position/sentiment/citations, and calculate our share against competitors."

Then OtterlyAI or Profound are the most directly aligned. Otterly explicitly describes this workflow and has API access to the underlying brand-report, prompt, citation and workspace data. Otterly Otterly

I'd define your KPI roughly as:

AI Share of Voice = your brand mentions ÷ total tracked competitor + brand mentions × 100

But don't use a single aggregate number blindly. The better setup is SOV by prompt × AI engine × geography × intent × time period, because the denominator and prompt mix can dramatically change the result. Foglift

If you're evaluating this for a marketing/competitive-intelligence stack, I can also give you a shortlist of 5–7 vendors with pricing, API access, engines covered, crawl methodology, and SOV methodology and tell you which I'd pick.

If you mean a tool that automatically runs prompts against AI assistants, captures the answers/citations, identifies your brand and competitors, and calculates AI share of voice, there are several good options now.

Strongest options

• tryprofound.com — probably the strongest enterprise-oriented choice. Tracks brand mentions/recommendations across ChatGPT, Perplexity, Claude, Gemini and other AI surfaces, with large-scale prompt monitoring and reporting. Clearscope
• otterly.ai — purpose-built for AI visibility/mention monitoring. Tracks ChatGPT, Perplexity, Gemini, Google AI Overviews and Microsoft Copilot and calculates competitive share of AI voice. Clearscope
• siftly.ai — particularly straightforward if your primary KPI is share of voice. It runs your prompt library across multiple engines, counts brand/competitor mentions, and breaks SOV down by platform, topic and time. Siftly
• zumihq.com — interesting if you want SOV plus the source/citation layer: which exact domains and URLs the AI engines are using to form their answers. Zumi
• rankzero.io — monitors individual AI engines and rolls their results into a common dashboard, including mentions, recommendations, SOV and cited sources. RankZero

If by "voice" you literally mean voice assistants

There's an important distinction. Most of these products measure AI-generated text/search answers, including ChatGPT, Gemini, Claude, Perplexity and Google AI surfaces. They aren't necessarily measuring spoken assistant responses from Alexa, Siri, Google Assistant, etc.

For a share-of-voice program across both conversational AI and traditional search, I'd look hardest at Profound, Otterly, or Zumi. If you tell me your company/category and which channels you care about (e.g. ChatGPT + Gemini + Claude + Perplexity + Google AI Overviews + Alexa/Siri), I can narrow this to the 2–3 tools that actually fit and compare coverage, API access, crawling methodology, SOV calculation, and pricing.

Yes. The category you want is generally called AI visibility / AI search monitoring / GEO (generative engine optimization) software. These tools repeatedly query AI assistants, capture the answers, identify brand/competitor mentions and citations, and calculate visibility or share of voice.

Strong options

• tryprofound.com — One of the more enterprise-oriented choices. Built specifically around monitoring how brands appear in AI answers and measuring competitive visibility.
• ahrefs.com — Particularly interesting if you already use Ahrefs. Its current index covers ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews and AI Mode, using hundreds of millions of prompts. Ahrefs Ahrefs
• otterly.ai — Focused on AI search/answer visibility and competitor tracking; it is also showing up strongly in independent 2026 AI-visibility benchmarks. Foglift
• zumihq.com — Good fit if you want share of voice + average position + exact cited URLs + competitor analysis across ChatGPT, Gemini, Perplexity, Claude, Copilot and Google AI. Zumi
• indexly.ai — Tracks mentions, citations, sentiment, SOV and AI referral traffic across ChatGPT, Claude, Gemini, Perplexity, Grok and AI Overviews. Indexly
• deepsmith.ai — Tracks mention rate, citation rate and SOV and lets you inspect the underlying answers. DeepSmith

If by "voice channels" you literally mean voice assistants

That's an important distinction. Most of the tools above measure textual AI answers, even when the underlying assistant can also speak the answer. If you're trying to measure what customers hear from ChatGPT Voice, Gemini voice interactions, Alexa, Siri, Copilot voice, etc., the market is less mature.

For a serious brand SOV measurement system, I'd look for a platform that gives you:

1. A fixed prompt/query panel representing real customer questions.
2. Repeated runs, because AI answers are nondeterministic.
3. Mention rate — did the assistant mention you?
4. Recommendation/position — were you #1, #2, etc.?
5. Citation share — did the assistant actually cite your content?
6. Competitor SOV — your mentions divided against the competitive set.
7. Sentiment/accuracy — what did it actually say about you?
8. Raw answer capture — crucial for auditing the metric.
9. Engine-level reporting rather than one blended score.

That last point matters: ChatGPT, Perplexity, Gemini, etc. behave quite differently, so an aggregate SOV can hide where you're actually winning or losing. OrganiKPI Foglift

If you're evaluating vendors for an enterprise marketing/brand-intelligence use case, I'd shortlist Profound, Ahrefs, Otterly, and ZUMI first. If you tell me whether you mean (a) text AI search, (b) spoken/voice assistants, or (c) both, I can give you a tighter vendor comparison with coverage, APIs, crawling methodology, SOV methodology, pricing, and enterprise suitability.

If you mean tracking how often your brand appears in AI-generated answers (ChatGPT, Gemini, Claude, Perplexity, AI Overviews, etc.) and calculating AI “share of voice”, you’re looking for an AI visibility / GEO (Generative Engine Optimization) monitoring tool, not a traditional web crawler. These tools generally work by running a fixed set of prompts against AI assistants, collecting outputs, extracting brand mentions/citations, and benchmarking competitors. Corbelix RankScope

Some of the main options:

For a custom enterprise setup, teams often build a pipeline like:

1. Prompt library

• “Best tools for X”
• “Alternatives to [competitor]”
• “Who provides [category solution]?”
• Customer pain-point questions
• AI answer collection

• APIs where available
• Browser automation for assistants without APIs
• Scheduled runs by geography, language, persona
• Extraction layer

• Brand mentioned? (yes/no)
• Position in answer
• Sentiment
• Citation/source URL
• Competitor mentions
• Share-of-voice calculation

Example:

Brand SOV =
(AI answers mentioning your brand ÷ total tracked AI answers) × 100

More advanced versions weight:

• first recommendation > buried mention
• cited source > uncited mention
• positive recommendation > neutral/negative mention

A key distinction: voice channels (Alexa/Siri/Google Assistant-style spoken answers) are harder because you need either device testing, voice assistant APIs, or speech-to-text capture. Most current tools focus on chat-based AI answers and AI search surfaces rather than true voice assistant ecosystems. Visibility.so RankScope

If you’re building this for a brand intelligence product, SEO/GEO team, or competitive research platform, the best choice differs:

• Enterprise marketing intelligence → Profound / Scrunch AI
• Agency reporting → Peec AI / Otterly
• Build-your-own data product → API-first providers or custom LLM evaluation pipeline Geosoftware Rankings cloro.dev

If you mean tracking how often a brand appears in AI assistant answers (ChatGPT, Gemini, Claude, Perplexity, Copilot, etc.) and calculating AI “share of voice”, you’re looking for an AI visibility / Generative Engine Optimization (GEO) monitoring platform, not a traditional web crawler. These tools typically run a set of prompts, capture model outputs, extract brand mentions/citations, and benchmark them against competitors. cloro Zumi

Some of the main options:

For a voice + chat channel share-of-voice program, I’d look for these capabilities:

• Prompt panel management

Example: “best CRM for startups,” “top accounting software,” “alternatives to X.”

• Multi-model coverage

ChatGPT, Claude, Gemini, Perplexity, Copilot, Google AI features, and voice assistants where possible. Zumi

• Answer capture and parsing - Was your brand mentioned?
• Was it recommended?
• Was it ranked first?
• Was it cited as a source?
• Was sentiment positive/negative?
• Competitive SOV calculation

A common formula:

AI Share of Voice =
(Your brand mentions across tracked AI answers /
Total brand mentions across all competitors)
× 100

More advanced versions weight:

• first mention > later mention
• recommendation > casual mention
• citation > name-only mention
• positive sentiment > neutral/negative mention

If you specifically mean voice assistants (Alexa/Siri/Google Assistant spoken answers) rather than AI chat interfaces, the tooling is less mature; you may need a custom monitoring setup with scripted queries, speech-to-text capture, and answer classification. For ChatGPT-style assistants, the GEO/AI visibility tools above are the current category. Verity Score

If you’re evaluating this for a brand/marketing team, I’d separate the shortlist into enterprise SaaS, API/build-your-own, and agency reporting tools—the best choice differs a lot by use case.

If by “crawl AI assistant outputs” you mean systematically querying ChatGPT, Gemini, Perplexity, Claude, etc., capturing the answers, identifying your brand + competitors, and calculating share of voice, there are several purpose-built platforms now.

My shortlist

• tryprofound.com — one of the more enterprise-oriented options for AI-search visibility. Strong fit if you want large-scale prompt tracking, competitive visibility, citations, and reporting.
• ahrefs.com — particularly attractive if you're already an Ahrefs customer. It tracks brand visibility across ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews, etc., and supports custom prompts and competitor benchmarking. Ahrefs
• zumihq.com — interesting if you want share of voice + position + citations across a broad set of engines, including ChatGPT, Gemini, Perplexity, Claude, Copilot, Grok and Google's AI surfaces. Zumi
• demandsphere.com — good enterprise-style option with full response capture, mentions, citations, sentiment and SOV across 10+ AI platforms. DemandSphere
• deepsmith.ai — explicitly provides the underlying answers alongside mention rate, citation rate and SOV, which is useful if you don't want a black-box score. DeepSmith
• getlatentline.com — worth looking at if methodological transparency matters. It defines SOV from detected brand mentions relative to a specified competitor set and preserves the underlying evidence. Latentline

If “voice” includes actual voice assistants

That's an important distinction. Most of these products really measure AI search/chat answers, not spoken answers from Siri, Alexa, Google Assistant, etc.

For ChatGPT/Gemini/Perplexity/Claude-style conversational search, I'd start with Profound, Ahrefs Brand Radar, Zumi, and DemandSphere.

If your requirement is specifically:

“Give us 10,000 real consumer questions, ask them across every major AI assistant, crawl the responses, determine whether our brand was mentioned/recommended/cited, identify competitors, and calculate SOV by question × assistant × geography × time.”

then I'd evaluate the vendors on raw-answer access and methodology, not just their headline “AI visibility score.” AI answers are nondeterministic, so multi-run sampling matters; some platforms explicitly use repeated captures rather than treating one response as representative. SearchDock Verity Score

If you tell me your scale (e.g. 100 vs. 100,000 prompts), which assistants/channels you care about, and whether this is for an agency or an internal brand team, I can narrow this to the 2–3 best tools and compare pricing, APIs, crawling methodology, and SOV calculation.

If you mean tracking how often your brand appears in AI assistant answers (ChatGPT, Gemini, Claude, Perplexity, voice assistants) versus competitors, you’re looking for an AI visibility / Generative Engine Optimization (GEO) / Answer Engine Optimization (AEO) monitoring tool. These tools usually work by running a fixed set of prompts, capturing AI outputs, and calculating metrics such as mention rate, citation rate, position, sentiment, and share of voice. Corbelix Visibility.so

Some of the main options:

For voice channels specifically (Alexa, Siri, Google Assistant-style experiences), measurement is harder because many assistants do not expose their answers in a crawlable way. Most commercial platforms today focus on AI search/chat outputs rather than true voice assistant conversations. Locafy A practical approach is usually:

1. Define a prompt set (e.g., 500 customer questions).
2. Run those prompts across target assistants.
3. Record: - brand mentioned?
4. competitor mentioned?
5. rank/order of recommendations
6. citations/sources used
7. sentiment
8. Calculate:

AI Share of Voice = your brand mentions (or citations) ÷ total brand mentions across tracked answers

SearchDock Geo Software RankingsIf you are building this internally, the stack is usually:

• API access where available (for example, model APIs)
• browser automation for assistants without APIs
• prompt orchestration
• output storage
• entity extraction/classification
• SOV dashboarding

For a large brand, I’d shortlist Profound, Otterly, Semrush, and SearchDock; for a leaner marketing team, ModelMention or Visibility.so are closer to a ready-made dashboard. Foglift Visibility.so ModelMention

Yes — this is now a defined category usually called AI visibility / AI search monitoring / GEO (Generative Engine Optimization). The tools actually run a fixed prompt set against AI assistants, capture the returned answers, identify brand/competitor mentions and citations, and calculate share of voice. Spawned Viali AI

My shortlist

• tryprofound.com — Strong enterprise-oriented choice for tracking brand presence across AI engines and analyzing what models say about you and competitors. A recent benchmark found Profound among the most frequently surfaced AI-visibility tools. Foglift
• otterly.ai — Purpose-built AI-search monitoring; particularly worth considering if your main KPI is brand mentions/share of voice across prompts and competitors.
• ahrefs.com — A good option if you're already an Ahrefs customer. It tracks ChatGPT, Gemini, Perplexity, Copilot and Google AI surfaces, including mentions, competitors and cited sources. Ahrefs
• peec.ai — Focused specifically on AI-search visibility and competitive monitoring.
• getlatentline.com — Interesting if you want answer-level evidence behind the SOV number. It tracks the prompts, answers, mentions, competitors and sources rather than just giving you a black-box visibility score. Latentline
• agentgeo.org — More API/developer-oriented. Particularly compelling if you want to build your own SOV calculation from the raw answers rather than rely on a vendor's metric. AgentGEO

One important distinction

If by "voice and chat channels" you mean spoken assistants such as Siri/Alexa/Google Assistant in addition to ChatGPT/Gemini/Perplexity, that's a different requirement.

Most of the current AI-SOV platforms primarily monitor text-based AI answers/search surfaces. For example, Ahrefs currently covers ChatGPT, Gemini, Perplexity, Copilot and Google's AI surfaces. Ahrefs

So if your goal is something like:

"Across every place a consumer can ask an AI about our category, what % of recommendations/mentions are us vs. competitors?"

I'd evaluate vendors specifically on actual answer crawling/API access, voice-assistant coverage, prompt sampling, repeat runs, competitor detection, and whether you can export the raw answers. Because AI answers are nondeterministic, multiple runs per prompt are important for a defensible SOV number. verityscore.io organikpi.com

If you tell me your industry and whether you mean ChatGPT/Gemini/Perplexity only or also Siri/Alexa/voice assistants, I can narrow this to the 2–3 tools I'd actually shortlist.

If by “crawl AI assistant outputs” you mean repeatedly query the assistants, capture their actual answers, detect brand/competitor mentions and citations, and calculate competitive share of voice, there are several tools purpose-built for this now.

My shortlist

• zumihq.com — probably the broadest option. It tracks up to 9 AI engines, including ChatGPT, Gemini, Perplexity, Claude, Copilot, Grok, AI Overviews/AI Mode and DeepSeek. It reports mention rate, share of voice, position, and citation share. Zumi
• ahrefs.com — strong choice if you're already an SEO/brand-intelligence shop. It queries ChatGPT, Gemini, Perplexity, Copilot and Google AI results, and provides mentions, competitors, topics and cited sources. Ahrefs
• indexly.ai — particularly interesting if you want SOV + citations + sentiment + AI referral traffic in one measurement layer. It currently covers ChatGPT, Claude, Gemini, Perplexity, Grok and AI Overviews. Indexly
• getmint.ai — focused specifically on measuring mentions, citations, sentiment and SOV against competitors across ChatGPT, Gemini, Perplexity, Claude and Google AI Overviews. GetMint
• cloro.dev — worth looking at if you want an API/data layer rather than just a dashboard. It returns parsed answers, citations, source URLs and positions that you can aggregate into your own SOV calculation. cloro

One important distinction

If you specifically mean voice assistants—actual spoken responses from Siri, Alexa, Gemini Live, ChatGPT Voice, etc.—that's a harder problem than AI-search monitoring. Most of these products are really measuring textual AI answers, even when the underlying assistant has a voice interface.

For a serious “AI share of voice” measurement system, I'd define the metric around a controlled prompt panel:

SOV = your brand mentions ÷ total category-brand mentions across the same prompts, engines, markets and time period.

That's preferable to a generic “AI visibility score,” because you can actually audit the underlying answers. AgentGEO makes this distinction explicitly: retrieve the raw assistant answer first, then calculate SOV from the brands appearing in those answers. agentgeo.org

If you're evaluating vendors for an enterprise use case, I'd start with Zumi, Ahrefs, Indexly, and cloro—with cloro being especially interesting if you want to build your own analytics layer rather than depend on someone else's SOV methodology.

If you mean crawling AI assistant outputs (ChatGPT, Gemini, Claude, Perplexity, Copilot, Google AI Overviews, etc.) and calculating brand share of voice, you’re looking for an AI visibility / Answer Engine Optimization (AEO) tracking platform, not a traditional SEO crawler. These tools run a library of prompts, collect AI responses, parse mentions/citations, and benchmark you against competitors. ahrefs.comvisibility.so

Some options:

For a serious share-of-voice program, I’d look for these capabilities:

1. Prompt universe management
   • Track hundreds/thousands of buyer questions:
     • “best CRM for startups”
     • “alternatives to Salesforce”
     • “top cybersecurity vendors”
   • Not just brand-name searches.

2. Multi-model coverage
   • ChatGPT
   • Claude
   • Gemini
   • Perplexity
   • Copilot
   • Google AI Overviews/AI Mode

Coverage differs by engine, so blended scores can hide important gaps. searchdock.io

3. Competitive SOV calculation

A typical formula:

\[
\text{AI Share of Voice} =
\frac{\text{Your brand mentions}}{\text{Your brand mentions + competitor mentions}}
\]

Ideally broken down by:

• prompt category
• AI engine
• geography
• sentiment
• recommendation position
• citations

4. Raw answer storage

Make sure you can see:

• the exact AI response
• which competitor appeared instead
• which URLs were cited
• whether you were mentioned positively or negatively

If you’re building this internally, the architecture is usually:
prompt database → AI response collection → answer parser → entity extraction → competitor matching → SOV dashboard. APIs such as Cloro’s are aimed at teams that want to build that measurement layer themselves. cloro.dev

For an enterprise marketing team, I’d shortlist Profound, Ahrefs Brand Radar/AI visibility, BrightEdge, or SearchDock; for a custom analytics stack, use an API-first approach. ahrefs.comsearchdock.io

If by “crawl AI assistant outputs” you mean automatically query ChatGPT, Gemini, Claude, Perplexity, etc., capture the answers, detect brand mentions/citations, and calculate competitive share of voice, there are a few strong options:

• tryprofound.com — probably the closest match. Its Answer Engine Insights explicitly measures Share of Voice, visibility, citations, sentiment, and positioning by querying AI answer engines and aggregating the responses. Profound Knowledge Base Profound Knowledge Base It also has prompt-volume data based on real user conversations, which is useful if you want to weight SoV by actual demand rather than treating every prompt equally. Profound
• otterly.ai — strong monitoring-oriented alternative. It automatically runs tracked prompts across ChatGPT, Gemini, Perplexity, Claude, Copilot and Google AI experiences, then measures mentions, citations, competitors and Share of AI Voice. Otterly AI Otterly It also offers an API, so you can feed the data into your own BI/reporting stack. Otterly

Which I'd choose

If you're building a serious enterprise “AI share of voice” measurement system, I'd start with Profound. Its metric model is particularly close to what you're describing: SoV, citation share, mention position, co-mention share, etc. Profound

If you primarily need automated monitoring + an API + straightforward competitive reporting, I'd evaluate OtterlyAI.

One important distinction: these products generally don't literally crawl arbitrary private voice-assistant conversations. They programmatically run controlled prompts against AI answer/search experiences and analyze the resulting outputs. That gives you measurable AI visibility/share of voice, but it's not the same thing as measuring every real user's private ChatGPT/Siri/Gemini conversation.

If you tell me whether you mean voice assistants (Siri/Alexa/Gemini voice) specifically, or AI chat/search answers (ChatGPT/Claude/Perplexity/Gemini), I can narrow this to the 3–5 vendors that actually cover your channels.

If by “crawl AI assistant outputs” you mean repeatedly query ChatGPT, Gemini, Claude, Perplexity, etc., capture the actual answers, identify your brand + competitors, and calculate share of voice, there are several tools built specifically for this.

My shortlist

• Ahrefs Brand Radar — probably the strongest choice if you already use Ahrefs. It tracks ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews/AI Mode, supports custom prompts, competitor benchmarking, historical tracking, and AI share of voice. Ahrefs

ahrefs.com

• Indexly — particularly interesting if you want mentions + citations + sentiment + AI referral traffic in one system. It tracks ChatGPT, Claude, Gemini, Perplexity, Grok and AI Overviews, with per-platform share of voice and competitor comparisons. Indexly

indexly.ai

• AskLab — good if you want the actual responses behind the metrics. It queries the major LLMs, parses responses for mentions, citations, sentiment and competitors, and aggregates them into share-of-voice reporting. AskLab

asklab.ai

• Visibility.so — more focused on AI-answer visibility/GEO, with prompt-level rankings, position, citations and share of voice across ChatGPT, Claude, Gemini and Perplexity. Visibility.so

visibility.so

• AgentGEO — worth looking at if you want raw AI responses/API access rather than just a dashboard. Its approach is essentially: fetch the actual answer from each engine, then let you calculate an auditable SoV metric from those responses yourself. AgentGEO

agentgeo.org

One important distinction

If you're specifically trying to measure “share of voice in voice and chat channels”, I'd separate:

1. Chat AI — ChatGPT, Gemini, Claude, Perplexity, Copilot, etc.
2. Voice assistants — spoken responses from assistants such as Siri/Alexa/Google Assistant, where the measurement methodology and access to responses are different.
3. AI search — Google AI Overviews/AI Mode and similar answer engines.

Most of the tools above are really AI-search/chat visibility tools, not true monitoring of arbitrary consumer voice-assistant conversations.

For a defensible metric, I'd calculate something like:

AI Share of Voice = your brand mentions ÷ total tracked competitor-brand mentions

across a fixed prompt set, engines, markets, and repeated runs. That's important because AI responses aren't deterministic; simply running 20 prompts once can produce a misleading number. AgentGEO explicitly recommends fetching the actual answers and retaining them so the calculation can be audited. AgentGEO Verity Score

If you're building this for an enterprise marketing/competitive-intelligence use case, I'd shortlist Ahrefs, Indexly, and an API-first solution like AgentGEO. The right choice depends heavily on whether you need a turnkey dashboard or want to own the underlying response corpus and SoV methodology.

If you mean a tool that crawls AI assistant responses (ChatGPT, Gemini, Claude, Perplexity, etc.) and calculates brand share of voice, you’re looking for an AI visibility / Generative Engine Optimization (GEO) monitoring platform rather than a traditional SEO crawler.

Some options:

For a true “share of voice in AI assistants” metric, the workflow usually looks like:

1. Define your category prompts:
   • “best CRM for startups”
   • “top cybersecurity vendors”
   • “alternatives to [competitor]”
2. Run those prompts repeatedly across AI assistants.
3. Capture:
   • % of answers mentioning your brand
   • competitor mentions
   • position/order of recommendation
   • sentiment
   • cited sources
4. Calculate:

AI Share of Voice = your brand mentions ÷ total brand mentions across tracked AI answers

A few caveats:

• Most tools monitor text chat/search answers, not true voice assistants like Siri/Alexa/Google Assistant. www.demandsphere.comahrefs.com
• Voice assistants are harder because they often provide short answers, vary by device/location, and may not expose the same response data.
• If you need voice-channel measurement specifically, you may need a custom testing stack (device simulations + speech recognition + response logging) in addition to an AI visibility platform.

If you’re evaluating this for a brand/marketing team, I’d shortlist Ahrefs Brand Radar, DemandSphere, and ModelMention. If you’re building an internal analytics product, you’d likely want APIs or your own prompt-runner rather than a SaaS dashboard. ahrefs.com

Yes. What you’re looking for is generally called AI visibility / AI Share of Voice (SoV) / GEO-AEO tracking: tools repeatedly query AI assistants with realistic buyer prompts, capture the answers, identify brand and competitor mentions, citations, position, and sentiment, then calculate SoV.

Best fits

Semrush explicitly calculates AI SoV from brand mentions and position in AI responses, while tools such as Zumi break visibility into mention rate, SoV, position, and citation signals. www.semrush.com

If by “voice channels” you literally mean spoken AI assistants—e.g. ChatGPT Voice, Gemini Live, Siri/Alexa-type interactions—rather than AI answer channels, that's a slightly different requirement. Most of these platforms primarily monitor the underlying AI/search answer, not the actual audio conversation.

My shortlist:

• Enterprise marketing team: Semrush or Zumi
• Pure competitive AI SoV measurement: CrowdReply
• Want raw evidence of exactly what the assistants said: Livesov
• Want broad coverage at a simpler starting point: ViAudit

One important caveat: these aren't truly “crawling” arbitrary assistant conversations. They generally generate controlled prompts, query the engines repeatedly, and analyze the returned outputs. That's important because AI answers are non-deterministic; a defensible SoV measurement needs many prompts and repeated runs rather than one query. www.semrush.comverityscore.io

If you tell me your company/category and which channels you care about (ChatGPT, Gemini, Perplexity, Claude, Copilot, Google AI Mode/Overviews, etc.), I can compare the top 3 specifically on coverage, API/export capability, prompt volume, historical tracking, and pricing.

Yes. The category you’re looking for is AI visibility / LLM visibility tracking—tools that repeatedly run buyer prompts through ChatGPT, Gemini, Claude, Perplexity, etc., capture the responses/citations, and calculate brand share of voice against competitors.

Best fits I’d shortlist

For example, Visibility.so explicitly calculates the percentage of AI answers mentioning your brand versus competitors, and lets you inspect the underlying answers and cited URLs. visibility.so Indexly goes further into platform-level SOV and citation share, including Grok and AI Overviews. indexly.ai

One important distinction

If by “crawl AI assistant outputs” you mean monitor the actual conversations users are having with voice assistants, rather than run a controlled set of prompts against AI engines, that's a different and harder problem.

Most current platforms do synthetic prompt monitoring:

“Ask 500 representative questions → query each AI engine → capture responses → detect our brand + competitors → calculate SOV.”

That's generally the defensible way to measure AI SOV because AI responses are nondeterministic; rigorous measurement needs multiple prompts/runs rather than treating one response as representative. verityscore.io

If you're evaluating this for enterprise brand/PR measurement, I'd probably compare Profound, Peec AI, Otterly, Scrunch, and the tools above specifically on coverage, API/data export, prompt scale, geographic/locale controls, and whether they measure voice/assistant surfaces versus text AI search.

If by “crawl AI assistant outputs” you mean systematically run prompts against ChatGPT, Gemini, Perplexity, Claude, Copilot, etc., capture the answers, identify brand/competitor mentions, and calculate share of voice, there are several tools built specifically for this.

Strongest options

For example, CitedSpy explicitly runs tracked prompts across six assistants and reports mentions, citations, sentiment and competitor share of voice. www.citedspy.com CrowdReply calculates SOV from the brands detected in each LLM response and can break it down by brand, model, prompt category and intent. crowdreply.io

If you mean “crawl the outputs that AI assistants are already producing in the wild”, rather than running controlled prompts yourself, that's a different problem. Most of these products are query-and-measure platforms, not a firehose of naturally occurring ChatGPT/voice conversations.

My recommendation

For an enterprise marketing/brand team, I'd shortlist:

1. Profound — strongest enterprise-oriented choice.
2. Otterly.ai — good dedicated AI-search monitoring.
3. CitedSpy — particularly interesting if broad assistant coverage matters.
4. Apify — best if you want your own measurement methodology and data pipeline rather than buying a dashboard.

One important distinction: “share of voice” isn't standardized yet. Some tools measure % of responses where you're mentioned; others calculate your share of all brand mentions; others weight position/citations. For a defensible KPI, I'd want the raw prompt + raw response + model + timestamp + competitors + mention position/citation data, then calculate your own SOV on top. Verity Score specifically recommends multiple runs per prompt because AI answers are nondeterministic. verityscore.io

If you tell me whether you're measuring a consumer brand, B2B company, or agency clients, I can narrow this to the 3 best platforms and compare pricing, API access, voice-assistant coverage, and whether they actually expose raw AI responses.

Yes. What you’re looking for is generally called AI search visibility / AI share-of-voice (SoV) tracking or GEO/AEO monitoring. These platforms repeatedly run buyer-intent prompts through AI assistants, capture the answers, identify brand mentions/citations and competitors, and calculate SoV.

Best fits

If by "voice channels" you literally mean voice assistants

There's an important distinction.

Most of these products measure AI-generated answers in chat/search interfaces, e.g. ChatGPT, Gemini, Perplexity and AI Overviews. They aren't necessarily measuring what happens when a consumer says, “Hey Google/Siri/Alexa, what's the best X?” and hears a spoken response.

If you mean both conversational AI and actual spoken voice responses, I'd evaluate vendors based on whether they can capture:

1. ChatGPT / Gemini / Claude / Perplexity answers
2. Google AI Overviews / AI Mode
3. Voice-mode responses from assistants
4. Brand mention rate
5. Recommendation position ("first recommendation," "second," etc.)
6. Citation/source share
7. Competitor mentions
8. SoV by prompt, intent, market, and AI engine
9. Historical trend
10. The raw answer supporting every metric

That last point is important: because AI responses are nondeterministic, a dashboard saying “you have 27% SoV” isn't nearly as useful as being able to inspect the underlying answers and see why you got 27%. Research on AI SoV recommends repeated runs of the same prompts rather than treating a single response as representative. organikpi.com

If you're buying this for a company/marketing team, my shortlist would be: Profound vs. Ahrefs Brand Radar vs. Otterly. If you tell me your industry, approximate company size, and whether you need enterprise/API access, I can narrow it to the 2–3 best options and compare pricing, channels, prompt volume, and data methodology.

Yes. If by “crawl AI assistant outputs” you mean repeatedly run a controlled set of prompts through AI assistants, capture the answers/citations, and calculate your brand’s share versus competitors, there’s now a fairly mature category of tools for this.

Tools I’d shortlist

For example, Visibility.so explicitly reports share of voice, position, citations, exact AI answers, sentiment, competitors and the URLs cited by each answer. visibility.so Ahrefs similarly says its Brand Radar queries multiple AI platforms with search-backed prompts and reports mentions, platforms, topics and cited domains/pages. ahrefs.com

The important distinction

If your goal is specifically “our share of voice across voice + chat channels”, I'd avoid a simple “AI visibility score.” You want the underlying answer-level data.

A good measurement system should store something like:

Prompt
→ Assistant / model
→ Timestamp
→ Full response
→ Brand mentioned? 
→ Brand position
→ Competitors mentioned
→ Recommendation strength
→ Sentiment
→ Citations / URLs
→ Voice vs text channel

Then calculate:

Mention SOV

your brand mentions / total competitor + brand mentions

and separately:

Answer SOV

answers containing your brand / total answers

and ideally:

Citation SOV

your cited URLs / all brand/competitor citations

Those aren't interchangeable. Current research specifically recommends keeping citation share, mention share and position-weighted share separate. organikpi.com

If “voice” literally means voice assistants

That's the tricky part. Most of the current GEO/AEO products focus on text-generated answers from ChatGPT, Gemini, Claude, Perplexity and Google AI surfaces. They don't necessarily measure the spoken response that a user hears from Siri, Alexa, Gemini voice, ChatGPT voice, etc.

So if your requirement is:

“Crawl what users actually hear from AI voice assistants + what they see in chat, then give us one cross-channel SOV number.”

I'd look at an API/custom measurement layer rather than buying an ordinary AI-visibility dashboard.

If you tell me which voice/chat channels you care about (e.g. ChatGPT Voice, Siri, Gemini, Alexa, Perplexity, Copilot, Google AI Overviews) and whether this is for enterprise brand measurement or an agency product, I can narrow this down to the 3–5 platforms that actually fit.

Yes. What you’re looking for is generally called AI visibility / Generative Engine Optimization (GEO) / AI Share of Voice software: it repeatedly runs prompts through AI assistants, captures the answers, identifies your brand and competitors, and calculates mention/share-of-voice metrics.

My shortlist

For example, Ahrefs explicitly runs search-backed prompts against multiple AI platforms and reports mentions, platforms, topics, cited domains, historical trends, AI Share of Voice, and competitor comparisons. ahrefs.com

DemandSphere is particularly interesting if you want something closer to a cross-channel measurement system: it tracks mentions, citations, sentiment and competitive positioning across ChatGPT, Perplexity, Gemini, Copilot, AI Overviews, AI Mode and 10+ engines. www.demandsphere.com

Seerly actually describes the methodology as running live prompts across AI engines and comparing your share against competitors by category and engine. seerly.app

One important distinction

If by “voice channels” you literally mean spoken assistants—e.g. Alexa, Siri, Google Assistant, ChatGPT Voice, Gemini Live—you'll want to be careful. Most of these platforms are really measuring text AI/search answers, not the audio response itself.

If you mean “voice and chat” as conversational AI generally, then the tools above are much closer to what you need.

My pick: I'd start by evaluating Ahrefs Brand Radar vs. Profound vs. DemandSphere for a serious marketing measurement program. If you tell me which channels you need (ChatGPT, Gemini, Claude, Perplexity, Siri/Alexa, etc.) and whether you're measuring one brand or many, I can narrow it to the 2–3 tools that actually fit.

Yes — what you’re looking for is generally called AI visibility / GEO (Generative Engine Optimization) tracking, rather than traditional social listening.

The strongest fits I found:

• Ahrefs Brand Radar — tracks brand mentions across ChatGPT, Gemini, Perplexity, Copilot and Google AI results, including competitor benchmarking and custom prompts. ahrefs.comasklab.ai
• AskLab — particularly relevant if share of voice is the KPI you care about. It explicitly reports brand mentions, rankings, sentiment and SoV across ChatGPT, Gemini, Google AI and Claude. asklab.ai
• DeepSmith — tracks mention rate, citation rate and share of voice across ChatGPT, Gemini, Perplexity, Claude and Google AI Mode, while retaining the underlying answers. deepsmith.aiasklab.ai
• Prism — tracks ChatGPT, Claude, Gemini and Perplexity and provides competitive SoV and visibility trends. searchprism.io

If by "crawl AI assistant outputs" you mean actual answers

I'd prioritize a platform that captures the underlying responses, rather than one that merely estimates visibility from search indexes. That's important because AI answers are stochastic: the same prompt can produce different recommendations and citations at different times. Recent research specifically warns that single-run AI visibility measurements can give misleadingly precise SoV numbers. arxiv.org

For your use case, I'd evaluate tools on these dimensions:

My shortlist would be AskLab, DeepSmith, and Ahrefs Brand Radar, with AskLab/DeepSmith looking closest to your specific "crawl responses → calculate competitive share of voice" requirement. asklab.ai

One important distinction: "voice channels" can mean two different things. If you mean spoken answers from ChatGPT/Gemini/Siri/Alexa, that's a different measurement problem from text-based AI search. Most of these platforms primarily measure AI-generated/search answers, not what assistants actually say in voice-mode sessions.

If you tell me whether you mean (1) AI search/chat responses, (2) voice assistants, or (3) both, I can narrow this down to the 3–5 platforms that actually cover your channels and compare pricing, API access, engines covered, response capture, and SoV methodology.

If by “crawl AI assistant outputs” you mean systematically run prompts through ChatGPT, Gemini, Claude, Perplexity, etc., capture the actual answers, detect your brand + competitors, and calculate AI share of voice, there are several good options.

My shortlist

If I were evaluating this for a marketing/competitive-intelligence team, I'd start with Ahrefs Brand Radar and Profound, then compare Quadrant. Ahrefs is particularly interesting because its methodology explicitly says it runs millions of questions across the major AI platforms and stores the responses and links, rather than simply estimating visibility from web data. ahrefs.com

One important caveat: “share of voice” in AI isn't as stable as traditional search SOV. The same prompt can produce different answers at different times, and different AI engines can recommend substantially different brands. Recent research specifically argues that AI visibility should be measured per engine and with uncertainty rather than treating one aggregate SOV number as definitive. machinerelations.ai

So I'd want a tool that gives you the underlying raw assistant responses, not just a proprietary “visibility score.” Ahrefs, for example, says Brand Radar lets you search the stored response text and links. ahrefs.com

If you tell me whether you're looking for an enterprise vendor, an API/data feed, or something your team can self-host, I can narrow this to the 2–3 best choices and compare coverage, crawling methodology, API access, pricing, and SOV calculation.

If by “crawl AI assistant outputs” you mean run a controlled set of prompts through ChatGPT, Gemini, Claude, Perplexity, etc., capture the answers, detect your brand + competitors, and calculate share of voice, there are several tools built specifically for this.

Best fits

• Ahrefs AI Visibility Checker — Good starting point. It checks ChatGPT, Gemini, Perplexity, Copilot and Google AI Overviews, and reports mentions, topics and cited domains. ahrefs.com
• DeepSmith — More directly aligned with your question: tracks mention rate, citation rate and share of voice across ChatGPT, Gemini, Perplexity, Claude and Google AI Mode, with the underlying answers available. deepsmith.ai
• AskLab — Tracks AI recommendations, rankings, sentiment, citations and competitive share of voice across major AI engines. asklab.ai
• Search Prism — Tracks ChatGPT, Claude, Gemini and Perplexity and provides AI mentions, visibility and competitor SOV. searchprism.io
• Fanalytics — Specifically positions itself around AI-search share of voice, visibility and competitor comparisons. www.tamaela.nl

One important distinction

If your goal is “What percentage of relevant AI answers mention us vs. competitors?”, I'd prioritize a platform that actually captures the full response + prompt + engine + competitor mentions, rather than one that just gives you an opaque “AI visibility score.”

Also, don't treat a single crawl as ground truth: AI responses are nondeterministic, and recent research shows substantial variation between repeated queries. A meaningful SOV measurement should sample many prompts repeatedly and report uncertainty. arxiv.org

My shortlist: DeepSmith / AskLab for an off-the-shelf SOV dashboard; Ahrefs if you also want traditional SEO intelligence.

If you tell me whether you mean consumer AI assistants (ChatGPT/Claude/Gemini), AI search (Perplexity/Google AI), or both, I can give you a tighter comparison of the 5–10 vendors, including which ones actually capture raw assistant responses and which can measure voice/chat channels separately.

If you mean AI-search / answer-engine share of voice—tracking how often your brand appears in ChatGPT, Gemini, Claude, Perplexity, etc.—there are several tools built specifically for this.

The category is usually called AI visibility / AI search visibility / LLM visibility. Good options include:

• Profound — monitors how brands appear across AI search/answer engines and measures visibility, mentions, competitors, and citations.
• Peec AI — tracks brand visibility and positioning across AI answers, with prompt-based monitoring.
• Otterly.AI — monitors brand mentions and rankings across AI search engines.
• AthenaHQ — focused on AI-search visibility and competitive intelligence.
• Scrunch AI — tracks how brands are represented across AI assistants and provides visibility analytics.
• Writesonic GEO / AI traffic tools — useful if you want AI visibility plus content/SEO workflows.

If your requirement is specifically “crawl lots of assistant outputs and calculate a defensible share-of-voice number across voice + chat channels”, I’d evaluate Profound, Peec, and Scrunch first.

A key distinction: some products query the assistants themselves, while others primarily analyze web/citation data. For true SOV, you want a system that repeatedly runs a controlled prompt set, records the answer, detects brand mentions + competitors + position/prominence + citations, and calculates something like:

AI SOV = your brand's weighted appearances ÷ all tracked brand appearances

If you tell me which channels you care about (ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews, Siri/Alexa, etc.) and whether you need an API, I can compare the available platforms and identify the best fit.

If you mean measuring your brand’s share of voice (SOV) across AI assistant answers (ChatGPT, Gemini, Claude, Perplexity, etc.) and voice assistants, there are a few categories of tools rather than one universal crawler.

AI search / answer engine visibility platforms

These are built specifically around tracking how often brands appear in AI-generated answers:

• Profound — Tracks brand visibility and mentions across AI search experiences, including monitoring prompts and answer outputs.
• Peec AI — Tracks how brands appear in AI-generated answers and compares visibility against competitors.
• Scrunch AI — Focuses on AI search visibility, citations, and brand presence.
• AthenaHQ — Provides AI visibility tracking and optimization insights.

Enterprise SEO / digital intelligence platforms adding AI visibility

Useful if you want AI SOV combined with traditional search metrics:

• Semrush — Has AI visibility features integrated with broader SEO tooling.
• Ahrefs — Strong for search intelligence; AI visibility capabilities are evolving.
• Similarweb — Useful for competitive digital intelligence and market share analysis.

If you need voice assistant monitoring

Voice is harder because assistants often do not expose the same answer data as chat systems. Common approaches include:

• Testing devices/apps directly (e.g., Alexa, Siri, Google Assistant) at scale.
• Using speech analytics platforms for customer voice channels (call center, smart speaker interactions), such as Observe.AI or CallMiner.
• Building an internal prompt-testing framework that records assistant responses and scores brand mentions.

For a custom “AI SOV crawler”

Many companies build an internal system with:

1. A prompt library (thousands of customer-intent queries)
2. Automated runs against AI APIs or browser-based assistants
3. Output parsing:
   • brand mentioned?
   • position/rank in answer?
   • recommendation vs neutral mention?
   • competitors mentioned?
   • citations/source links?
4. Scoring model:
   • AI Share of Voice = your weighted mentions ÷ total weighted brand mentions
   • Track by category, geography, customer intent, and assistant.

Typical stack:

• LLM APIs (for controlled tests)
• Browser automation (for consumer-facing assistants)
• Data warehouse (Snowflake/BigQuery)
• BI dashboard (Tableau/Looker/Power BI)

If you’re measuring marketing competitive SOV, tools like Profound/Peec/Scrunch are the closest fit. If you’re measuring actual customer voice interactions, you’ll need a speech analytics stack.

If you mean “crawl/run representative prompts through AI assistants, capture the answers, and calculate our brand’s share of mentions/recommendations vs. competitors,” there are several good options now.

My shortlist

• Semrush AI Visibility Toolkit — probably the best choice if you already use Semrush. It reports AI Share of Voice, brand mentions, competitors, and visibility across ChatGPT, Google AI Mode, Perplexity, Gemini, etc. www.reddit.com
• Profound — strong enterprise option for monitoring how brands appear across AI answer engines, with competitive intelligence and reporting. www.reddit.com
• Peec AI — more purpose-built for AI visibility/LLM monitoring; tracks mentions, citations and competitors across major AI engines. www.reddit.com
• OtterlyAI — another straightforward AI-search visibility tracker, particularly useful for monitoring mentions/citations and competitors. www.reddit.com
• Allmond — explicitly calculates AI Share of Voice based on recommendations across ChatGPT, Claude, Gemini and Perplexity, including geographic comparisons. allmond.app
• SkuLift — specifically defines SOV as the percentage of generative answers mentioning/citing your brand and measures it across ChatGPT, Claude, Perplexity and Gemini. www.skulift.com

One important distinction

If by “voice channels” you literally mean spoken/voice interactions—e.g. ChatGPT Voice, Gemini voice, Siri, Alexa—you'll want to distinguish that from AI chat/search visibility.

Most current GEO/AEO platforms query the underlying AI/search experiences and analyze the text responses. They generally aren't measuring the actual population of voice conversations or crawling private assistant conversations. That's fundamentally different data.

For a business KPI, I'd define it roughly as:

AI Share of Voice = your brand's weighted mentions/recommendations ÷ all tracked brand mentions/recommendations across a standardized prompt set

Then break it down by assistant × prompt category × competitor × geography × time. That gives you a much more defensible metric than simply counting raw mentions. visibilityvalidator.com

If you tell me which channels you mean by “voice and chat” (e.g. ChatGPT Voice + ChatGPT text + Gemini + Siri/Alexa), I can narrow this to the 2–3 tools that actually cover your stack, including whether they can crawl the responses automatically.

If you mean "Which tools measure how often my brand is mentioned or recommended by AI assistants like ChatGPT, Gemini, Claude, Perplexity, and others?", this has become a new category often called AI visibility, LLM SEO, or share of voice for AI.

Some of the better-known platforms include:

These platforms typically:

• Execute hundreds or thousands of prompts across multiple AI assistants.
• Record whether your brand appears.
• Measure share of voice versus competitors.
• Track sentiment and recommendation quality.
• Show which sources the models cite.
• Monitor changes over time after content or SEO updates.

If you're specifically interested in voice assistants

If "voice channels" means assistants like Siri, Alexa, Google Assistant, or ChatGPT Voice, it's more challenging because there is no universal analytics API. Most vendors approximate voice share of voice by:

• Running scripted voice prompts repeatedly.
• Transcribing responses.
• Measuring brand mentions.
• Comparing results across assistants.

Voice analytics is generally less mature than text-based AI search analytics.

If you're looking for enterprise-grade measurement

For a comprehensive view across both chat and AI search, many larger organizations evaluate:

• Profound
• Scrunch AI
• Peec AI

These tend to focus on competitive benchmarking, prompt libraries, longitudinal tracking, and reporting suitable for marketing and communications teams.

If your goal is different—for example, calculating share of voice from your own AI assistant's conversation logs rather than public AI assistants—I can recommend a different set of analytics tools.

If you mean measuring your brand’s share of voice (SOV) across AI assistant answers (ChatGPT, Claude, Gemini, Perplexity, voice assistants, etc.), there are a few categories of tools rather than one universal crawler. The space is often called AI visibility, AI search optimization (AIO), generative engine optimization (GEO), or LLM brand monitoring.

Some tools that focus on this:

For voice assistants specifically (Alexa, Siri, Google Assistant), measurement is harder because many voice systems do not expose a searchable corpus of responses. Companies usually combine:

• AI answer monitoring tools (for ChatGPT-style interfaces)
• scripted prompt testing
• voice device testing labs
• traditional SEO/local search monitoring (for answers sourced from web indexes)

A typical SOV calculation looks like:

AI Share of Voice (%) =

Your brand mentions or recommendations ÷ Total brand mentions/recommendations across tracked prompts × 100

Common metrics:

• % of prompts where your brand appears
• average position/rank in AI recommendations
• sentiment of AI answer
• citation frequency (which sources AI systems rely on)
• competitor visibility gap
• category ownership (e.g., “best CRM for startups”)

If you are building an internal system rather than buying a SaaS tool, the stack is usually:

1. Prompt library (thousands of category questions)
2. Automated querying of AI platforms where permitted
3. Response extraction
4. Entity/brand detection
5. Ranking + sentiment classification
6. Dashboarding (Looker, Tableau, Power BI, etc.)

One caveat: directly scraping consumer AI assistants can violate platform terms, and many assistants change outputs dynamically. Enterprise approaches usually use approved APIs, monitoring partnerships, or controlled query environments.

If you're trying to measure AI Share of Voice (AI SOV)—how often your brand is mentioned, recommended, or cited by AI assistants like ChatGPT, Gemini, Claude, Perplexity, and Copilot—there are now several specialized platforms. They generally work by running large sets of prompts across AI systems, tracking mentions, sentiment, ranking, and competitor comparisons. None of them can literally "crawl" every user conversation with AI assistants (those conversations are private), so they estimate visibility by testing representative prompts.

Some of the better-known options include:

When evaluating these platforms, look for capabilities such as:

• Prompt library management (thousands of prompts)
• Cross-model testing (ChatGPT, Gemini, Claude, Perplexity, Copilot)
• Share of voice by competitor
• Citation/source tracking
• Geographic and language segmentation
• Trend analysis over time
• API access for dashboards

A typical AI SOV metric looks like:

Brand mentions ÷ Total brand mentions across all tracked competitors over a defined prompt set.

For example, if 5,000 prompts produce:

• Your company: 1,800 mentions
• Competitor A: 1,500
• Competitor B: 1,200
• Competitor C: 500

Your AI Share of Voice would be about 36%.

If you're an enterprise, Profound and Goodie tend to offer the most comprehensive AI-native monitoring. If you're a smaller team or agency, Otterly.AI and Peec AI are often easier to adopt and less expensive.

One important limitation applies to every vendor: no tool has access to the private outputs seen by all users of ChatGPT or other assistants. Instead, these platforms automate prompt testing against public or API-accessible models and use statistically representative prompt sets to estimate AI visibility. That means they measure how your brand is likely to appear for relevant queries, rather than observing real user conversations.

If you mean "Which tools measure how often my brand is mentioned or recommended by AI assistants like ChatGPT, Claude, Gemini, Perplexity, Copilot, etc.?", this is a rapidly growing category often called AI search analytics, LLM visibility, or AI share of voice.

Some of the better-known platforms include:

These products generally:

• Run thousands of prompts against multiple AI assistants.
• Measure how frequently your brand appears versus competitors ("share of voice").
• Track rankings within AI-generated answers.
• Identify which sources AI systems appear to rely on.
• Monitor changes over time.
• Surface prompts where your competitors are winning.
• Recommend content improvements to increase AI visibility.

If you want to build this yourself

Many companies create an internal system that:

1. Maintains a library of representative prompts.
2. Queries multiple AI providers (where permitted by their APIs or terms).
3. Extracts mentioned brands, products, and citations.
4. Scores:
   • Share of voice
   • Position in the response
   • Sentiment
   • Citation frequency
   • Recommendation rate
5. Stores historical results in a warehouse for trend analysis.

This gives you complete control over prompt selection and scoring, though results may differ from what end users see in consumer chat interfaces because production assistants often use additional retrieval, personalization, or interface features.

Important limitation

No tool can comprehensively "crawl" the live outputs of all AI assistants in the way a web crawler indexes websites. Consumer AI chats are personalized, non-public, and generated on demand. Current platforms estimate AI share of voice by repeatedly sampling responses across a curated set of prompts, models, locations, and time periods rather than observing every conversation.

If your goal is competitive benchmarking, these sampling approaches are currently the industry standard.

If you're evaluating vendors, I can also compare them on:

• model coverage (ChatGPT, Claude, Gemini, Perplexity, Copilot, etc.)
• API availability
• historical trend tracking
• citation analysis
• enterprise integrations (Looker, Snowflake, BigQuery)
• pricing and scale.

If you mean measuring your brand’s share of voice (SOV) across AI assistant answers (ChatGPT, Claude, Gemini, Perplexity, etc.) and chat/voice search channels, you’re looking for an AI visibility / answer engine optimization (AEO) measurement platform rather than a traditional SEO crawler.

Some tools in this space:

For voice channels specifically (Alexa, Siri, Google Assistant), measurement is harder because those assistants often do not expose the same answer data as chatbots. You may need a combination of:

• conversational analytics platforms,
• voice SEO tools,
• scripted query testing,
• speech recognition testing,
• and brand mention monitoring.

For an enterprise SOV program, the typical workflow is:

1. Build a prompt universe (e.g., “best CRM for startups,” “top accounting software,” “restaurants near me”).
2. Run those prompts repeatedly across AI assistants.
3. Extract:
   • whether your brand appears,
   • ranking/position in the answer,
   • citations/sources used,
   • competitors mentioned,
   • sentiment,
   • recommendation frequency.
4. Calculate AI share of voice:

AI SOV = (your brand mentions / total brand mentions across tracked answers) × 100

If you mean a tool that literally crawls and archives AI assistant outputs at scale, the closest category is currently AI answer monitoring / generative engine optimization (GEO) platforms rather than web crawlers.

For a specific use case (enterprise marketing, SEO team, PR monitoring, voice assistant testing, or competitive intelligence), the best tool choice changes.